Poor control of acute pain after surgery and in emergency departments persists, even though it increases costs, generates complications and can lead to chronic pain. Rigorous pain assessment is fundamental for improving pain management, but current methods have significant limitations in precision and sensitivity. Moreover, pain scales lack a true constant unit amount and are often hard for patients to use. This research program will establish, evaluate and validate a new scaling methodology for acute pain based on Item Response Theory and Structural Equation Modeling. This methodology will include growth curve modeling to characterize acute pain as a process of decay over time characterized by an initial value and a rate of change. It will compare the scaling performance of the new system against the standard method for clinical pain assessment in post-operative and emergency department settings. The pain scaling system based on Item Response Theory should demonstrate significantly better discriminant validity, significantly better measurement precision, and smaller standard errors of measurement than the standard measurement method. To expedite clinical application, the investigators will develop, optimize and validate Dynamic Adaptive Testing, a form of computerized adaptive testing, to maximize assessment efficiency for the new system. The new measurement methods will provide pain scaling sufficiently precise for use with individual patients, a constant unit amount so that scores compare directly across patients and settings, a profile characterization of acute pain, and strong validity. The results of this work will facilitate pain research, improve the management of acute pain, and help identify patients with acute pain who are at risk for developing chronic pain.